The Department of Defense's future vision for Network Centric Operations (NCO) is intended to increase combat control by networking relevant entities across a battlefield. This new vision implies large amounts of information sharing and collaboration across different entities. An example of a futuristic NCO scenario is one in which a group of heterogeneous Unmanned Vehicles (UVs) are supervised by a single operator using NCO technology. In this type of complex command and control (C2) scenario, UV operators will be subjected to vast amounts of information as compared to today's command and control scenarios.
Therefore, this vision brings with it a new problem that must be addressed: How to maintain an adequate workload to avoid information overload and resulting loss of situation awareness. Currently, C2 technologies that allow the operator to control multiple UVs in a NCO scenario are rapidly increasing. The development of these new C2 technologies generates the tendency to exponentially increase the ratio of UVs to operators. However, if systems are inadequately designed or are used beyond their design capabilities, they will not adequately control for increased workload, which in turn will cause the operator to become overloaded and lose situation awareness. It is critical that decision makers develop predictive models of human and system performance to evaluate the adequacy of a system's design to satisfy specific mission requirements. It would be better to know in advance the optimum team size of UVs for a given mission scenario before it actually occurs, which would allow for improved allocation of UV and operator resources by decision makers.